Machine Learning Engineer, Safety and Customer Care AI

Навыки

• AI-агенты
• Дообучение моделей
• LLM
• Machine Learning
• Python
• PyTorch
• Регрессионное тестирование

Задачи

• Conduct literature review and build post-training framework and lifecycle
• Curate and process human and synthetic data for SFT/LoRA/RLHF/RLAIF/RLVR, and iterate on model quality for real support and safety tasks
• Develop, evaluate, and productionize AI agents, designing tools, state, and control flow in LangGraph (or equivalent) and taking them through the full agent development lifecycle
• Build and scale evaluation frameworks, golden sets, rubric-based grading, LLM-as-judge where appropriate, and regression testing
• Ship models and agents into real-time production, with the monitoring and guardrails needed to operate them safely at millions of interactions a month
• Experience
• Post-training experience with open-source models
• Agentic development experience. Built and shipped agents with LangGraph or equivalent frameworks, and comfort with the full agent development lifecycle
• Experience with AI/LLM evaluation. Designed metrics and built offline/online evaluation for generative systems
• Experience deploying ML/AI applications to real-time production use cases
• Preferred
• Experience applying ML/AI to customer support or trust & safety workflows — agent assist, routing, resolution recommendation, or abuse/safety detection
• PhD in Computer Science, Machine Learning, Statistics, or a related technical field
• Publications at top-tier peer-reviewed research venues (e.g., NeurIPS, ICML, ICLR, ACL, CVPR)
• At Lyft, our purpose is to serve and connect
• We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive
• The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers
• We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection
• Agentic AI is at the center of how we scale that mission
• We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution
• SCC brings together ML, data, backend, and product engineers alongside data scientists and operations partners to transform these systems
• As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help

Требования

• 3+ years of industry experience in applied ML/AI, inclusive of an MS or PhD in Computer Science, Machine Learning, Artificial Intelligence or a related technical field
• Hands-on familiarity with fine-tuning and preference-tuning paradigms such as SFT, LoRA, RLHF, RLAIF, and RLVR
• Strong programming skills in Python and hands-on experience with PyTorch

Условия

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy
• The policy allows team members to take off as much time as they need (with manager approval)
• Hourly team members get 15 days paid time off, with an additional day for each year of service
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs
• Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits and Lyft ride credits
• Lyft is committed to creating an inclusive workforce that fosters belonging
• Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy
• Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind
• Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process
• Please contact your recruiter if you wish to make such a request
• Lyft highly values having employees working in-office to foster a collaborative work environment and company culture
• This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays
• Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role
• Your recruiter can share more information about the various in-office perks Lyft offers
• Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
• The expected base pay range for this position in the Toronto area is CAD $118,800 - CAD $148,500, not inclusive of potential equity offering, bonus or benefits
• Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location
• Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process

Паспорт вакансии

История публикации

Откуда что взялось

Отмечено то, что вывели мы. Без пометки — значение назвал работодатель.

Почему на этом месте в выдаче

Порядок выдачи объявлен контрактом: свежесть решает между днями, полнота и зарплата — внутри дня.